1PEOD: Padé Estimated Optimum (radar) Detector

Abstract — In this paper, an expression of the optimum non-Gaussian radar detector is derived from the non-Gaussian SIRP model (Spheri-cally Invariant Random Process) clutter and a Padé approximation of the characteristic function of the SIRP. The SIRP model is used to perform coherent detection and to modelize the non-Gaussian clutter as a com-plex Gaussian process whose variance is itself a positive random variable (r.v.). The probability density function (PDF) of the variance character-izes the statistics of the SIRP and after performing a Padé approximation of this PDF from reference clutter cells we derive the so-called Padé Esti-mated Optimum (Radar) Detector (PEOD) without any knowledge about the statistics of the clutter. We evaluate PEOD performance for an un-known target signal embedded in K-distributed clutter and compare with optimum detectors performance (optimum in particular clutter statistics such as Optimum K Detector- OKD- in K-distributed clutter). I